Optimal Operation of PV-integrated Reconfigurable Microgrids and Computational Burden

Abstract

This paper addresses the significant potential of reconfiguration in renewable-based microgrids (MGs), emphasizing not only its practical benefits but also the computational challenges involved. Firstly, a nonlinear non-convex model developed for the optimal operation of photovoltaic (PV)-integrated reconfigurable microgrids (RMGs). To guarantee the optimality of the solutions, we further refine the model by extracting a mixed-integer linear programming model, achieved through the implementation of piecewise linearization technique and approximation. To substantiate the efficacy and importance of reconfiguration in MGs, comparative analyses of two distinct case studies-one with reconfiguration and one without are presented. These comparisons not only highlight the operational improvements afforded by reconfiguration but also shed light on the computational complexities encountered. Moreover, the impact of different radiality method selections on the computational time is explored. Our findings validate the significant role of reconfiguration in enhancing the performance of renewable-based MGs while also emphasizing the critical consideration of computational burden in the design and implementation of such systems.